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Tuning the Pd-catalyzed electroreduction of CO<sub>2</sub> to CO with reduced overpotential
Han, Zishan,Choi, Changhyeok,Tao, Hengcong,Fan, Qun,Gao, Yuannan,Liu, Shizhen,Robertson, Alex W.,Hong, Song,Jung, Yousung,Sun, Zhenyu The Royal Society of Chemistry 2018 Catalysis Science & Technology Vol.8 No.15
<P>Developing selective and efficient catalysts is highly desirable for electrochemical CO2 reduction (ECR) to fuels and chemicals. Pd can strongly bind *COOH but weakly bind *CO, thus resulting in CO as a product. However, proton reduction also occurs severely on the surface of Pd, leading to low CO selectivity. Here we found that the ECR to CO can be greatly enhanced by controlling the Pd-ceria interface and doping with tellurium atoms. Notably, a very high mass activity of 92 mA mgPd<SUP>−1</SUP> (at 1.0 V <I>vs.</I> reversible hydrogen electrode) for CO formation was achieved, significantly surpassing previously reported Pd catalysts (35 mA mgPd<SUP>−1</SUP> at −1.0 V). The Pd catalysts comprising CeOx displayed more positive onset potentials than the Pd catalysts in the absence of CeOx, enabling ECR to CO at −0.6 V (<I>vs.</I> RHE). The modified Pd catalyst also afforded an unprecedented CO faradaic efficiency of over 84% at a low Pd loading (@@<@@3 wt%). Density functional theory calculations revealed that the Pd atoms located between the Te dopant and CeO2 promoted CO formation, thus improving CO2 conversion efficiency.</P>
Cellular and Molecular Mechanisms of Intestinal Fibrosis
Wu Xiaomin,Lin Xiaoxuan,Tan Jinyu,Liu Zishan,He Jinshen,Hu Fan,Wang Yu,Chen Minhu,Liu Fen,Mao Ren 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.3
Intestinal fibrosis associated stricture is a common complication of inflammatory bowel disease usually requiring endoscopic or surgical intervention. Effective anti-fibrotic agents aiming to control or reverse intestinal fibrosis are still unavailable. Thus, clarifying the mechanism underpinning intestinal fibrosis is imperative. Fibrosis is characterized by an excessive accumulation of extracellular matrix (ECM) proteins at the injured sites. Multiple cellular types are implicated in fibrosis development. Among these cells, mesenchymal cells are major compartments that are activated and then enhance the production of ECM. Additionally, immune cells contribute to the persistent activation of mesenchymal cells and perpetuation of inflammation. Molecules are messengers of crosstalk between these cellular compartments. Although inflammation is necessary for fibrosis development, purely controlling intestinal inflammation cannot halt the development of fibrosis, suggesting that chronic inflammation is not the unique contributor to fibrogenesis. Several inflammation-independent mechanisms including gut microbiota, creeping fat, ECM interaction, and metabolic reprogramming are involved in the pathogenesis of fibrosis. In the past decades, substantial progress has been made in elucidating the cellular and molecular mechanisms of intestinal fibrosis. Here, we summarized new discoveries and advances of cellular components and major molecular mediators that are associated with intestinal fibrosis, aiming to provide a basis for exploring effective anti-fibrotic therapies in this field.
Instance segmentation with pyramid integrated context for aerial objects
Juan Wang,Liquan Guo,Minghu Wu,Guanhai Chen,Zishan Liu,Yonggang Ye,Zetao Zhang 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.3
Aerial objects are more challenging to segment than normal objects, which are usually smaller and have less textural detail. In the process of segmentation, target objects are easily omitted and misdetected, which is problematic. To alleviate these issues, we propose local aggregation feature pyramid networks (LAFPNs) and pyramid integrated context modules (PICMs) for aerial object segmentation. First, using an LAFPN, while strengthening the deep features, the extent to which low-level features interfere with high-level features is reduced, and numerous dense and small aerial targets are prevented from being mistakenly detected as a whole. Second, the PICM uses global information to guide local features, which enhances the network's comprehensive understanding of an entire image and reduces the missed detection of small aerial objects due to insufficient texture information. We evaluate our network with the MS COCO dataset using three categories: airplanes, birds, and kites. Compared with Mask R-CNN, our network achieves performance improvements of 1.7%, 4.9%, and 7.7% in terms of the AP metrics for the three categories. Without pretraining or any postprocessing, the segmentation performance of our network for aerial objects is superior to that of several recent methods based on classic algorithms.